On the behavior of the robust bayesian combination operator and the significance of discounting

Abstract We study the combination problem for credal sets via the robust Bayesian combination operator. We extend Walley's notion of degree of imprecision and introduce a measure for degree of conflict between two credal sets. Several examples are presented in order to explore the behavior of the robust Bayesian combination operator in terms of imprecision and conflict. We further propose a discounting operator that suppresses a source given an interval of reliability weights, and highlight the importance of using such weights whenever additional information about the reliability of a source is available

RTiS 2005 Proceedings of Real Time in Sweden

Abstract not availabl

The effect of optimizing engine control on fuel consumption and roll amplitude in ocean-going vessels : An experimental study

We use data-generated models based on data from experiments of an ocean-going vessel to study the effect of optimizing fuel consumption. The optimization is an add-on module to the existing diesel-engine fuel-injection control built by Q-TAGG R&D AB. The work is mainly a validation of knowledge-based models based on a priori knowledge from physics. The results from a simulation-based analysis of the predictive models built on data agree with the results based on knowledge-based models in a companion study. This indicates that the optimization algorithm saves fuel. We also address specific problems of adapting data to existing machine learning methods. It turns out that we can simplify the problem by ignoring the auto-correlative effects in the time series by employing low-pass filters and resampling techniques. Thereby we can use mature and robust classification techniques with less requirements on the data to demonstrate that fuel is saved compared to the full-fledged time series analysis techniques which are harder to use. The trade-off is the accuracy of the result, that is, it is hard to tell exactly how much fuel is saved. In essence, however, this process can be automated due to its simplicity. “System för bränslebesparing på stora fartyg”, 2013-00301, Vinnova Forska & Väx 201

Virtual Full Replication for Wireless Sensor Networks

We propose to use a distributed real-time database with Virtual Full Replication by Adaptive Segmentation, for whiteboard communication in a sensor network with mobile sink nodes. Sensor networks are large scale applications with limited resources, so they need scalable propagation of sensor data, both to the users inside the network and to the network edges. Virtual full replication enables scalable and adaptive propagation of sensor data, by bounding resource usage to the current data needs. We use a two-tiered wireless sensor network, where each sensor value is published in the distributed database at gateways of the upper tier. Mobile users search for sensor data only at the gateways, which limits the search space.

Virtual Full Replication: Achieving Scalability in Distributed Real-Time Main-Memory Systems

To achieve better scalability in a fully replicated distributed main-memory database, we propose support for virtual full replication. Full replication is often necessary for availability and predictability in critical embedded applications. In the fully replicated database, however, all updates are sent to all nodes, regardless of whether the data is ever used at every node. Virtual full replication is a concept that improves scalability without changing the application 's assumption of having access to a fully replicated database. We support virtual full replication by segmenting the database and allowing segments to have individual degrees of replication. This decreases the replication effort, lowers overall memory requirements for data and decreases node recovery time. Typical scenarios include distributed databases with many nodes, where often only a small number of the nodes need to share the same subset of information. We have previously specified a segmentation syntax for specifying important application semantics and outlined an implementation. Here, we analyze the potential scalability improvements in such an architecture

Using Distributed Active Real-Time Database Functionality

Abstract — We present a list of requirements that need to be addressed by an infrastructure for information fusion where applications have real-time requirements. The requirements are grouped into configuration requirements, temporal requirements, and robustness requirements. We show how the functionality of a distributed active real-time database system (DARTDBS) can meet many of the given requirements, and therefore, argue that it is suitable for use in an information-fusion infrastructure with real-time requirements. The design of a particular DARTDBS, the DeeDS architecture and prototype, is presented as proof of concept. A comparison with some alternative infrastructures is briefly discussed. We describe a small distributed real-time simulation experiment using DeeDS as infrastructure, and discuss open questions such as how to deal with uncertainty management of information sources, recovery of information fusion nodes, and harmonizing data structures from different information sources. Index Terms — Information fusion infrastructure, distributed active real-time database system, distributed real-time simulation. I

Combination testing strategies: A survey

Combination strategies are test case selection methods that identify test cases by combining values of the different test object input parameters based on some combinatorial strategy. This survey presents 16 different combination strategies, covering more than 40 papers that focus on one or several combination strategies. This collection represents most of the existing work performed on combination strategies. This survey describes the basic algorithms used by the combination strategies. Some properties of combination strategies, including coverage criteria and theoretical bounds on the size of test suites, are also included in this description. This survey paper also includes a subsumption hierarchy that attempts to relate the various coverage criteria associated with the identified combination strategies